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Record W3048108834 · doi:10.1017/s0022215120001747

The UK national registry of ENT surgeons with coronavirus disease 2019

2020· article· en· W3048108834 on OpenAlexaff
Kate Stephenson, Leigh J. Sowerby, Claire Hopkins, Neelja Kumar

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2020
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineDiseaseCoronavirus disease 2019 (COVID-19)Personal protective equipmentCoronavirusFamily medicineMedical emergencySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Emergency medicineInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: ENT surgeons are likely to be at high risk of coronavirus disease 2019 exposure. METHODS: A national registry of UK ENT surgeons with suspected or confirmed coronavirus disease 2019 was created with the support of ENT UK. Voluntary entry was made by either the affected individual or a colleague, using a web-based platform. RESULTS: A four-month data collection period is reported, comprising 73 individuals. Coronavirus disease 2019 was test-confirmed in 35 respondents (47.9 per cent). There was a need for hospitalisation in two cases (2.7 per cent) and tragically one individual died. Symptom onset peaked in March. The majority suspected their exposure to have been in the workplace, with a significant proportion attributing their disease to a lack of personal protective equipment at a time before formal guidance had been introduced. CONCLUSION: The registry suggests that a significant number of ENT clinicians in the UK have contracted coronavirus disease 2019, and supports the need for tailored personal protective equipment guidance and service planning.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.180

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.298
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2020
Admission routes1
Has abstractyes

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